Reverse Bayesianism: Revising Beliefs in Light of Unforeseen Events
CESifo, Munich, 2020
CESifo Working Paper No. 8662
Bayesian updating is the dominant theory of learning. However, the theory is silent about how individuals react to events that were previously unforeseeable or unforeseen. Building on a recently developed axiomatic framework to analyze such situations, we test if subjects update their beliefs according to “reverse Bayesianism”, under which the relative likelihoods of prior beliefs remain unchanged after an unforeseen event materializes. We develop two experiments that entail unforeseen events and find that participants do not systematically deviate from reverse Bayesianism. However, we do find well-known violations of Bayesian updating. Decision makers seem to be ex ante unaware - they do not expect outcomes that they have not yet observed or have not been informed about. At the same time, we find instances of both increased and decreased awareness after exposure to unforeseen events.
Behavioural Economics